Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden but provides minimal behavioral details. It mentions 'persist the output', hinting at storage or creation, but doesn't disclose permissions needed, side effects, rate limits, or what 'persist' entails (e.g., where saved, overwrite risks). This is inadequate for a tool that likely creates persistent data.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads key information ('generate a protocol or governance prompt') and avoids redundancy. Every word contributes to the purpose, making it appropriately sized with zero waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given complexity (2 parameters, no annotations, nested 'options' object) and an output schema (which reduces need to explain returns), the description is incomplete. It covers the basic action but lacks details on behavioral traits, parameter usage, and context vs siblings. It's minimally viable but has clear gaps in guidance and transparency.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate but adds no parameter details. It mentions 'protocol or governance prompt', aligning with the 'type' enum, but doesn't explain 'options' or their purpose. With 2 parameters (one required, one with enum) and no schema descriptions, the baseline is 3 as it partially addresses 'type' but leaves 'options' unexplained.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('generate') and resource ('protocol or governance prompt'), specifying it uses 'Refactoring MCP builders' and 'persist the output'. It distinguishes from siblings like 'refactoring_mcp_get_prompt' (retrieval) and 'refactoring_mcp_list_prompts' (listing), but doesn't explicitly contrast them, so it's not a perfect 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention scenarios for 'protocol' vs 'governance' types, prerequisites, or when to choose other tools like 'refactoring_mcp_get_prompt' for retrieval. Usage is implied by the action but lacks explicit context or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool returns documents in a bundle but doesn't explain what a 'bundle' entails (e.g., format, structure, size limits) or any operational traits like performance, authentication needs, or error handling. This leaves significant gaps in understanding how the tool behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's function without any fluff or redundant information. It's front-loaded and wastes no words, making it easy to parse quickly while conveying the essential action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has zero parameters, 100% schema coverage, and an output schema exists, the description's job is lighter. However, it lacks details on what the 'bundle' output entails (e.g., format, content scope), and with no annotations, it doesn't address behavioral aspects like safety or performance. This makes it minimally adequate but incomplete for full understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to add parameter details, as there are none to document. It appropriately focuses on the tool's purpose without unnecessary parameter explanations, meeting the baseline for a parameterless tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Return') and resource ('all Refactoring MCP guidance documents in one bundle'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'refactoring_mcp_list_documents' or 'refactoring_mcp_get_document', which likely serve related but distinct purposes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'refactoring_mcp_list_documents' and 'refactoring_mcp_get_document', it's unclear whether this tool is for bulk retrieval, comprehensive overviews, or other specific contexts, leaving users to guess based on the name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It states 'Fetch', implying a read operation, but doesn't disclose behavioral traits such as authentication needs, rate limits, error handling, or what 'by key' entails (e.g., is it a unique identifier?). The description is minimal and lacks crucial operational context for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded, with every word contributing to the core purpose. No wasted verbiage or structural issues.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema (which handles return values), the description's minimalism is somewhat acceptable. However, with no annotations and low schema description coverage, it lacks completeness for operational use—e.g., it doesn't clarify the document types or usage context. The presence of an output schema raises the baseline, but gaps in behavioral and parameter details keep it at an adequate level.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds minimal meaning beyond the input schema. It mentions 'by key', which hints that the 'document' parameter acts as a key, but the schema already defines it as an enum of document types. With schema description coverage at 0%, the description doesn't compensate by explaining what each enum value represents or how the key is used. Since there's only one parameter, the baseline is 4, but the lack of added semantic value reduces it to 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Fetch' and the resource 'Refactoring MCP document by key', making the purpose understandable. However, it doesn't distinguish this tool from its sibling 'refactoring_mcp_get_prompt' or 'refactoring_mcp_get_bundle', which likely fetch different types of resources. The description is specific but lacks sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'refactoring_mcp_list_documents' and 'refactoring_mcp_get_prompt', there's no indication of when fetching a document is preferred over listing or fetching prompts. No context or exclusions are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('Retrieve') but lacks details on permissions, error handling, rate limits, or what 'stored' implies (e.g., access controls). This is a significant gap for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste, front-loading the core action ('Retrieve') and resource. It's appropriately sized for a simple tool, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema (which handles return values), low parameter complexity, and no annotations, the description is minimally complete. It states what the tool does but lacks behavioral and usage context, making it adequate but with clear gaps in guidance and transparency.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 0%, but the description adds minimal value by implying the 'id' parameter is used to identify a prompt. However, it doesn't explain the ID format, source, or constraints, leaving the schema to fully define the parameter. With one parameter and low coverage, this meets the baseline but doesn't compensate adequately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Retrieve') and resource ('a stored Refactoring MCP prompt'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'refactoring_mcp_list_prompts' or 'refactoring_mcp_get_document', which would be needed for a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention siblings like 'refactoring_mcp_list_prompts' for listing prompts or 'refactoring_mcp_get_document' for other resources, leaving the agent to infer usage context without explicit direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool lists documents but does not specify if this is a read-only operation, if it requires authentication, what the output format is (though an output schema exists), or any rate limits. This leaves significant gaps in understanding the tool's behavior beyond its basic function.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that directly states the tool's purpose without any redundant or verbose language. It is front-loaded and efficiently conveys the essential information, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (zero parameters, output schema provided), the description is adequate but minimal. It covers the basic purpose but lacks behavioral context (e.g., permissions, output details) that would be helpful for an agent, especially since no annotations are present. The existence of an output schema mitigates some gaps, but overall completeness is moderate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the input schema coverage is 100%, so there is no need for parameter explanation in the description. The baseline for zero parameters is 4, as the description appropriately does not include unnecessary param details, and the schema fully handles the lack of inputs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('List') and resource ('published Refactoring MCP guidance documents'), making the tool's purpose understandable. However, it does not differentiate from sibling tools like 'refactoring_mcp_list_prompts' or 'refactoring_mcp_get_document', which would require specifying scope or format distinctions to achieve a score of 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. For instance, it does not clarify if this should be used for browsing all documents versus using 'refactoring_mcp_get_document' for specific ones, or how it relates to 'refactoring_mcp_list_prompts'. The description lacks any context or exclusions for usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'returns metadata' but doesn't specify what that metadata includes (e.g., names, IDs, timestamps), whether it's paginated, if there are rate limits, or any authentication requirements. This leaves significant gaps in understanding the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every part of the sentence contributes directly to understanding the tool's function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description is adequate for a basic list operation. However, without annotations and with sibling tools present, it lacks guidance on usage and behavioral details like metadata structure or pagination, making it minimally viable but incomplete for optimal agent use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to compensate for any parameter gaps, so it meets the baseline. However, it doesn't add any parameter-related context beyond what's implied by 'all prompts', which is minimal but sufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Return metadata') and resource ('all prompts stored in the MCP server'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this from sibling tools like 'refactoring_mcp_get_prompt' or 'refactoring_mcp_list_documents', which would require mentioning it returns a list/collection rather than individual items.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'refactoring_mcp_get_prompt' for retrieving a single prompt or 'refactoring_mcp_list_documents' for listing documents instead of prompts, leaving the agent without context for tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool returns but doesn't disclose any behavioral traits, such as whether it's a read-only operation, if it has rate limits, authentication needs, or potential side effects. For a status-checking tool, this is a significant gap, as users might assume it's safe without explicit confirmation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise and front-loaded, consisting of a single sentence that directly states the tool's function without any fluff. Every word earns its place by clearly conveying the action and resource, making it efficient and easy to parse for an AI agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (0 parameters, simple purpose) and the presence of an output schema (which should cover return values), the description is minimally adequate. However, it lacks context on usage scenarios or behavioral traits, which could be important for a status tool in a server environment. It meets the baseline but doesn't go beyond to provide full completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters, and the input schema has 100% description coverage (though empty), so there's no need for parameter details in the description. The description appropriately avoids redundant information, earning a high score for not cluttering with unnecessary param semantics, as it focuses on the tool's purpose instead.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Return') and resource ('MCP server metadata and uptime'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'refactoring_mcp_get_bundle' or 'refactoring_mcp_get_document', which might also retrieve metadata, though those seem focused on specific content rather than server status.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention context, prerequisites, or exclusions, such as whether it's for monitoring, debugging, or initialization. With sibling tools like 'refactoring_mcp_list_documents' that might serve different purposes, this lack of guidance could lead to confusion in tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.